Realtime triggering framework

ABSTRACT

A computer-implemented method generates a trigger registration for a selected triggering type. The generated trigger registration is stored in a triggering persistency. A received event from an event persistency is analyzed and data associated with the analyzed event is compared with the triggering persistency. Based on the comparison and using a pattern execution framework, an enterprise threat detection (ETD) pattern is processed to perform actions responsive to the received event.

BACKGROUND

Enterprise threat detection (ETD) typically allows analyzing log datafrom various enterprise computing systems over known ETD patternsindicating threats to the computing systems. Currently the ETD patternsare processed on a periodic basis, for example, every ten minutes. Forthis example timeframe, it can take up to ten minutes before a threatcan be detected using the EDT pattern; potentially allowing data theft,damage, etc. (including possibly to the ETD system itself) to occurwithin the enterprise computing system until the threat detection systemprocesses log data against the ETD patterns at the next periodthreshold. However, increasing the period frequency (for example, toprocess an ETD pattern every minute or more frequently), raisescomputational and resource loads on one or more computers due to theincreased frequency of processing. As some types of enterprise computingsystem attacks occur very infrequently (for example, less than once permonth), an approach to increase the period frequency is in conflict witha goal to decrease computer operation costs.

SUMMARY

The present disclosure describes methods and systems, includingcomputer-implemented methods, computer program products, and computersystems for realtime enterprise threat detection (ETD).

In an implementation, a computer-implemented method generates a triggerregistration for a selected triggering type. The generated triggerregistration is stored in a triggering persistency. A received eventfrom an event persistency is analyzed and data associated with theanalyzed event is compared with the triggering persistency. Based on thecomparison and using a pattern execution framework, an enterprise threatdetection (ETD) pattern is processed to perform actions responsive tothe received event.

The above-described implementation is implementable using acomputer-implemented method; a non-transitory, computer-readable mediumstoring computer-readable instructions to perform thecomputer-implemented method; and a computer system comprising a computermemory interoperably coupled with a hardware processor configured toperform the computer-implemented method/the instructions stored on thenon-transitory, computer-readable medium.

The subject matter described in this specification can be implemented inparticular implementations so as to realize one or more of the followingadvantages. First, execution occurs in realtime or in substantiallyrealtime. Immediately after a log entry arrives in an event persistency,an alert can be detected and reported if applicable to the log entry.Second, execution of an ETD pattern can be on demand. With triggered ETDpatterns there are no unneeded scheduled ETD pattern executions thatresults in negative findings. This saves computing (hardware andsoftware) resources. Third, ETD patterns are executed in parallel withprocessing threads. Different ETD patterns triggered through the samelog entry/entries are executed at the same time. This allows a potentialthreat to be reported sooner than running each ETD pattern sequentially.In sequential execution some delays would occur. Fourth, complex andexpensive ETD patterns can be divided into a chain of simple ETDpatterns. This division can reduce complexity and allows a chain to bebroken if one of the chained ETD patterns results in no findings. Fifth,at some point in the execution of an ETD pattern chain, a fork (forexample, calling several ETD patterns simultaneously) can be performed.This forking permits faster execution and receipt of ETD patternexecution results. Other advantages will be apparent to those ofordinary skill in the art.

The details of one or more implementations of the subject matter of thisspecification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating data/process flow for a realtimeenterprise threat detection (ETD) triggering framework, according to animplementation.

FIG. 2 is a flow chart illustrating trigger creation activity for therealtime ETD triggering framework, according to an implementation.

FIG. 3 is a block diagram illustrating additional detail of thedispatcher of the realtime ETD triggering framework, according to animplementation.

FIGS. 4A and 4B illustrate a flowchart of an example method for realtimeETD threat detection, according to an implementation.

FIG. 5 is a block diagram of an exemplary computer system used toprovide computational functionalities associated with describedalgorithms, methods, functions, processes, flows, and procedures asdescribed in the instant disclosure, according to an implementation.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

The following detailed description describes a realtime triggeringframework for realtime enterprise threat detection (ETD), and ispresented to enable any person skilled in the art to make and use thedisclosed subject matter in the context of one or more particularimplementations. Various modifications to the disclosed implementationswill be readily apparent to those skilled in the art, and the generalprinciples defined herein may be applied to other implementations andapplications without departing from scope of the disclosure. Thus, thepresent disclosure is not intended to be limited to the described orillustrated implementations, but is to be accorded the widest scopeconsistent with the principles and features disclosed herein.

For the purposes of this disclosure, the term “real-time,” “real time,”“realtime,” “real (fast) time (RFT),” “near(ly) real-time (NRT),” “quasireal-time,” or similar terms (as understood by one of ordinary skill inthe art) means that an action and a response are temporally proximatesuch that an individual perceives the action and the response occurringsubstantially simultaneously. For example, the time difference for aresponse to display (or for an initiation of a display) of datafollowing the individual's action to access the data may be less than 1ms, less than 1 sec., less than 5 secs., etc. While the requested dataneed not be displayed (or initiated for display) instantaneously, it isdisplayed (or initiated for display) without any intentional delay,taking into account processing limitations of a described computingsystem and time required to, for example, gather, accurately measure,analyze, process, store, and/or transmit the data.

ETD typically allows analyzing data (for example, log data) from variousenterprise computing systems over known ETD patterns indicating threatsto the computing systems. While the following description focused on theuse of log data for analysis, other types of data associated with ETDcomputing systems can also be leveraged for ETD analysis using thedescribed methodology. Currently ETD patterns are processed on aperiodic basis, for example, every ten minutes. For this exampletimeframe, it can take up to ten minutes before a threat can be detectedfrom analysis of entries in log files using one or more ETD patterns.This delay can potentially allow data theft, damage, etc. (includingpossibly to the ETD system itself which would further compromise ETD) tooccur within the enterprise computing system until the threat detectionsystem processes log data against particular ETD patterns at the nextprocessing period threshold. However, increasing the processing periodfrequency (for example, to process an ETD pattern every minute or morefrequently) to mitigate this concern, raises computational and resourceloads on one or more computers due to the increased frequency ofprocessing. As some types of enterprise computing system attacks occurvery infrequently (for example, less than once per month), an approachto increase the period frequency is in direct conflict with a goal todecrease computer operation costs.

The disclosure describes a solution framework where an ETD pattern isexecuted on-demand. For purposes of this disclosure, “on-demand” meansthat ETD pattern execution is triggered as soon as content has arrivedin a log file that is related to the ETD pattern or a particular eventhas occurred. For example, in an ETD pattern detection, a log file entryhaving a particular value in one of the fields is written to a log or analert is raised by the processing of another ETD pattern (eventdetection) which triggers a subsequent ETD pattern(s) to execute. As afurther example, a log entry could include the assignment of aparticular role (for example, a supervisory or an administrative role)to a user. The assignment of the particular role could, for example,have been detected using a first ETD pattern and can trigger the use ofa second ETD pattern used to detect the criticality of this roleassignment (for example: 1) who is the particular user?; 2)identification of which user assigned the particular role?; and 3) whatactions has the user been performing since the particular role wasassigned?). If the role assignment is determined to have been critical(for example, the user himself/herself assigned the new role tothemselves, the user has accessed a high-security database in theenterprise computing system, etc.), the second ETD pattern can initiategeneration of an alert (for example, executing additional computer code,processes, etc. to generate an alert or notifying the first ETD patternto initiate generation of an alert, locking down particular enterprisecomputing systems, temporarily suspending the role assignment, etc.).

FIG. 1 is a block diagram illustrating an example data/process flow fora realtime enterprise threat detection (ETD) triggering framework 100,according to an implementation. The data/process flow contains aforensic lab: pattern facet 102, trigger persistency 104, dispatcher106, event persistency 108, processing thread(s) 110 (hereinafter“threads”), and pattern execution framework 112. As will be appreciatedby those of ordinary skill in the art, the example data/process flow isone possible arrangement of components and data/process flow. Othercomponents and data/process flows consistent with this disclosure arepossible and are considered to be within the scope of this disclosure.

In addition to the ETD scheduled triggering pattern “Periodically” (asdescribed above), a new ETD pattern execution mode called “Trigger” isintroduced. The trigger mode allows an ETD pattern to be executed “ByEvent” or “By Pattern.”

FIG. 2 is a flow chart illustrating trigger creation activity 200 forthe realtime ETD triggering framework, according to an implementation.For clarity of presentation, the description that follows generallydescribes method 200 in the context of the other figures in thisdescription. However, it will be understood that method 200 may beperformed, for example, by any suitable system, environment, software,and hardware, or a combination of systems, environments, software, andhardware as appropriate. In some implementations, various steps ofmethod 200 can be run in parallel, in combination, in loops, or in anyorder.

At 202, an ETD triggering configuration application (for example aforensic lab configuration application—not illustrated) that isassociated with the forensic lab: pattern facet 102 is used by an ETDpattern designer to configure a triggering mode (for example, either“Periodically” or “Trigger”) and associated trigger(s). In the case oftriggering mode “Trigger,” a selection can then be made of “By Event” or“By Pattern.” From 202, method 200 proceeds to 204.

At 204, for a configured trigger (either by event or by pattern), atrigger registration (for example, an entry in the example table“Trigger” below) is generated and added to a registration list (notillustrated) stored in the trigger persistency 104.

The trigger persistency 104 is typically a database (for example, eithera conventional or in-memory database) used to store the registrationlist of trigger registrations. In other implementations, the triggerpersistency 104 can use any type of data storage and data structureconsistent with this disclosure. In one particular implementation, atrigger entry (each entry in the entity Trigger corresponds to oneregistration) could be defined similarly to:

entity Trigger { key PatternId : Binary(16); key TriggerName :String(5000); key TriggerType : String(5000); ChangeTimestamp :UTCTimestamp; Namespace : String(500); };where TriggerName is either a PatternId of the triggering ETD pattern(in case of triggering by Pattern) or a SemanticEventId (in case oftriggering by Event). From 204, method 200 stops.

Returning to FIG. 1, a dispatcher 106 (see below), whose response timeis relatively significant in the ETD triggering framework 100, has onlyread to the trigger persistency 104. For example, read access in anin-memory database is extremely fast. Write accesses to the triggerpersistency 104 are performed during ETD pattern design time where highperformance is not a significant factor.

In the example of a selected “By Event” trigger, one or more values of asemantic event are set (registered content), which are used as triggercontent, and an ETD pattern name (registered ETD pattern) identified toexecute if the trigger is activated. If the semantic event contains aregistered value, the trigger is activated and the registered ETDpattern is executed.

In the example of a selected “By Pattern” trigger, the registration listtypically contains content relevant for ETD pattern triggering(registered content) and an identified ETD pattern name to execute(registered ETD pattern). With the registered content and the registeredETD pattern, the registration list can be used to quickly andefficiently check whether registered content has been detected. If theregistered content is detected. If the registered content is detected,the registered ETD pattern is executed.

For example, if example registrations (entries in entity Trigger)resemble:

PatternId TriggerName TriggerType ChangeTimestamp Namespace A XByPattern . . . . . . A Y ByPattern . . . . . .After execution of pattern X, pattern A is executed if the execution ofpattern X results in an Alert. The same is also true for pattern Y, thatis, if after execution of pattern Y, any alerts occur, then the patternA is called.

In the example of a selected “By Events” trigger, the exampleregistration could resemble:

PatternId TriggerName TriggerType ChangeTimestamp Namespace ASemEventNameB ByEvent . . . . . . A SemEventNameC ByEvent . . . . . .In this case the Dispatcher (more precisely, the “By Event” TriggerManager 304—see FIG. 3) checks in the events persistency 108 if logswith Entries corresponding to SemEventNameB and SemEventNameC arrived.If so, then pattern A is called. Technical implementations are typicallyefficient enough to allow fast execution (for example, every second) tocheck if any log entries arrived that correspond to TriggerNames.

ETD patterns are data objects saved in JSON format in our patternpersistency. ETD patterns contain paths. Each path contains subsets,which represent WHERE conditions (for example “filter only systems A, B,and C” or “do not consider IP addresses starting with “.10,” etc.).Paths can be connected over references (which are represented by JOINS).Each pattern is translated into an SQL query, meaning that a patternexecution is a SQL query execution. Alerts are pattern results or queryexecution results.

After execution of an ETD pattern (any type of ETD pattern—scheduled ortriggered) and if the executed ETD pattern results in an alert(s), thepattern execution framework 112 calls the dispatcher 106 and passes thePatternId of the executed ETD pattern. Dispatcher 106 checks in thetrigger persistency 104 for registrations for the received PatternId(for example, using field “TriggerName”) with a triggering type of “ByPattern” (for example, using field “TriggerType”). If YES, thencorresponding ETD patterns are executed in parallel using differentthreads 110.

The dispatcher 106 is a computational daemon thread or a job executingat a high frequency (for example, every 1 sec.). The dispatcher 106accesses and analyzes one or more events in the event persistency (forexample, arriving log entries) and determines, using the registrationlist stored in the trigger persistency 104, whether arriving content inone or more events has been associated with a trigger (whether by eventor by pattern). Given the dispatcher 106's computational speed, thesystem is considered to run in realtime or in substantially realtime. Ifa determination is made that such content has arrived, corresponding ETDpatterns are selected for processing and threads 110 established forprocessing the corresponding ETD patterns. With this methodology,execution of an ETD pattern is “on demand,” meaning when correspondingevent data demands that an ETD pattern be triggered to be executed. Withtriggered ETD patterns there are no unneeded scheduled ETD patternexecutions that result in negative findings. This saves computing(hardware and software) resources.

Each of the selected ETD patterns is processed in a separate thread 110to permit parallelization of ETD responses. Different ETD patternstriggered through the same log entry/entries are executed at the sametime in parallel. This allows a potential threat to be reported morequickly than running through ETD patterns in some sequential order.

Dispatcher 106 reads “By Events” registrations from the triggerpersistency 104. Each registration, in addition to a PatternId, containsa SemanticEventId. In the event persistency 108, there is acorresponding field containing a SemanticEvent. The dispatcher 106determines (for example, every 1 second) if, for the SemanticEventIds,any events containing a corresponding SemanticEvent arrived in the eventpersistency 108. If the determination is TRUE, a list of suchregistrations is created. For each of these registrations, a thread 110is allocated by the dispatcher 106 that processes an ETD pattern. Eachthread 110 typically processes one ETD pattern one time and is stopsfollowing the processing to free any used computational resources(hardware and software).

A persistency call (triggering and event) is typically performed in onequery call for efficiency. Analysis is strictly based on triggeringpersistency 104 registrations.

In typical implementations, a latest insertion timestamp of read events(from the event persistency 108) is persisted (for example, in adatabase, memory storage, etc.), so that the next reading from the eventpersistency 108 (for example, 1 second later) picks up immediately afterthe stored timestamp.

The event persistency 108 is typically a database (for example, either aconventional or in-memory database) used to store log data for anenterprise computing system. In other implementations, the eventpersistency 108 can use any type of data storage and data structureconsistent with this disclosure. In some implementations, the eventpersistency 108 can be used to persist a subset of log data for anenterprise computing system (for example, only data applicable tocertain defined periodic or trigger triggering while other enterprisecomputing system data can be stored in a different data store foranalysis). This subset configuration might allow for faster processingof particular data, while the dispatcher 106 processed data for theremaining data using other data stores acting as additional eventpersistencies 108. In some implementations, more than one dispatcher 106could be configured to execute in different threads/jobs to permitparallelization of the dispatcher for increased performance. In theseimplementations, the multiple dispatchers 106 can be configured tocommunicate with each other regarding, for example, status, triggeredtriggers, ETD pattern execution status, metrics, results, etc.

In a typical implementation, events are stored in a column table in theevent persistency 108. This table is typically partitioned on a dailybasis, so that, for example, up to 2 billion entries can be storeddaily. Since the dispatcher 106's reading access time for the eventpersistency 108 is very short (for example, 1 second), the response timeto evaluate if any ETD patterns should be triggered typically takesapproximately 2 ms, which permits realtime ETD pattern triggering.

In a typical implementation, an example structure of the eventpersistency (field “TechnicalLogEntryType contains mentionedSemanticEvent that corresponds to SemanticEventId saved in fieldTriggerName in the trigger persistency 104):

entity Events { Id : UUID; Timestamp : UTCTimestamp; TechnicalGroupId :UUID; TechnicalLogEntryType : ShortString; TechnicalNumber : Integer64;TechnicalNumberRange : ShortString; TechnicalTimestampOfInsertion :UTCTimestamp; AttackName : ShortString; AttackType : ShortString;CorrelationId : ShortString; CorrelationSubId : ShortString; Event :ShortString; EventLogType : ShortString; EventMessage : LongString;EventScenarioRoleOfActor : ShortString; EventScenarioRoleOfInitiator :ShortString; EventSeverityCode : ShortString; EventSourceId :ShortString; EventSourceType : ShortString; GenericAction : ShortString;GenericCategory : ShortString; GenericDeviceType : ShortString;GenericExplanation : LongString; GenericGeolocationCodeActor :ShortString; GenericGeolocationCodeTarget : ShortString; GenericOrder :Integer64; GenericOutcome : ShortString; GenericOutcomeReason :ShortString; GenericPath : LongString; GenericPathPrior : LongString;GenericPurpose : ShortString; GenericRiskLevel : ShortString;GenericScore : Integer64; GenericSessionId : ShortString; GenericURI :LongString; NetworkHostnameActor : ShortString; NetworkHostnameInitiator: ShortString; NetworkHostnameIntermediary : ShortString;NetworkHostnameReporter : ShortString; NetworkHostnameTarget :ShortString; NetworkHostDomainActor : ShortString;NetworkHostDomainInitiator : ShortString; NetworkHostDomainIntermediary: ShortString; NetworkHostDomainReporter : ShortString;NetworkHostDomainTarget : ShortString; NetworkInterfaceActor :ShortString; NetworkInterfaceTarget : ShortString; NetworkIPAddressActor: ShortString; NetworkIPAddressInitiator : ShortString;NetworkIPAddressIntermediary : ShortString; NetworkIPAddressReporter :ShortString; NetworkIPAddressTarget : ShortString;NetworkIPBeforeNATActor : ShortString; NetworkIPBeforeNATTarget :ShortString; NetworkMACAddressActor : ShortString;NetworkMACAddressInitiator : ShortString; NetworkMACAddressIntermediary: ShortString; NetworkMACAddressReporter : ShortString;NetworkMACAddressTarget : ShortString; NetworkNetworkPrefixActor :ShortString; NetworkNetworkPrefixTarget : ShortString; NetworkPortActor: Integer; NetworkPortInitiator : Integer; NetworkPortIntermediary :Integer; NetworkPortReporter : Integer; NetworkPortTarget : Integer;NetworkPortBeforeNATActor : Integer; NetworkPortBeforeNATTarget :Integer; NetworkProtocol : ShortString; NetworkSessionId : ShortString;NetworkSubnetIdActor : UUID; NetworkSubnetIdInitiator : UUID;NetworkSubnetIdIntermediary : UUID; NetworkSubnetIdReporter : UUID;NetworkSubnetIdTarget : UUID; NetworkZoneActor : ShortString;NetworkZoneTarget : ShortString; ParameterDirection : ShortString;ParameterDirectionContext : ShortString; ParameterName : ShortString;ParameterNameContext : ShortString; ParameterDataType : ShortString;ParameterDataTypeContext : ShortString; ParameterType : ShortString;ParameterTypeContext : ShortString; ParameterValueNumber : Integer64;ParameterValueNumberContext : Integer64; ParameterValueNumberPriorValue: Integer64; ParameterValueString : LongString;ParameterValueStringContext : LongString; ParameterValueStringPriorValue: LongString; ParameterValueDouble : BinaryFloat;ParameterValueDoublePriorValue : BinaryFloat; ParameterValueTimestamp :UTCTimestamp; ParameterValueTimestampPriorValue : UTCTimestamp;PrivilegeIsGrantable : Boolean; PrivilegeName : ShortString;PrivilegeType : ShortString; PrivilegeGranteeName : ShortString;PrivilegeGranteeType : ShortString; ResourceContainerName : ShortString;ResourceContainerType : ShortString; ResourceContent : LongString;ResourceContentType : ShortString; ResourceCount : Integer64;ResourceName : ShortString; ResourceNamePrior : ShortString;ResourceRequestSize : Integer64; ResourceResponseSize : Integer64;ResourceSize : Integer64; ResourceType : ShortString;ResourceSumCriteria : ShortString; ResourceSumOverTime : BinaryFloat;ResourceUnitsOfMeasure : ShortString; ServiceAccessName : ShortString;ServiceFunctionName : ShortString; ServiceReferrer : ShortString;ServiceRequestLine : LongString; ServiceType : ShortString;ServiceVersion : ShortString; ServiceApplicationName : ShortString;ServiceExecutableName : ShortString; ServiceExecutableType :ShortString; ServiceInstanceName : ShortString; ServiceOutcome :ShortString; ServicePartId : ShortString; ServiceProcessId :ShortString; ServiceProgramName : ShortString; ServiceTransactionName :ShortString; ServiceUserAgent : ShortString; ServiceWorkflowName :ShortString; SystemIdActor : ShortString; SystemIdInitiator :ShortString; SystemIdIntermediary : ShortString; SystemIdReporter :ShortString; SystemIdTarget : ShortString; SystemTypeActor :ShortString; SystemTypeInitiator : ShortString; SystemTypeIntermediary :ShortString; SystemTypeReporter : ShortString; SystemTypeTarget :ShortString; TimeDuration : Integer64; TimestampOfEnd : UTCTimestamp;TimestampOfStart : UTCTimestamp; TriggerNameActing : ShortString;TriggerNameTargeted : ShortString; TriggerTypeActing : ShortString;TriggerTypeTargeted : ShortString; UserLogonMethod : ShortString;UsernameActing : ShortString; UsernameInitiating : ShortString;UsernameTargeted : ShortString; UsernameTargeting : ShortString;UsernameDomainNameActing : ShortString; UsernameDomainNameInitiating :ShortString; UsernameDomainNameTargeted : ShortString;UsernameDomainNameTargeting : ShortString; UsernameDomainTypeActing :ShortString; UsernameDomainTypeInitiating : ShortString;UsernameDomainTypeTargeted : ShortString; UsernameDomainTypeTargeting :ShortString; UserIdActing : UUID; UserIdInitiating : UUID;UserIdTargeted : UUID; UserIdTargeting : UUID; }.

Turning to FIG. 3, FIG. 3 is a block diagram illustrating additionaldetail of the dispatcher of the realtime ETD triggering framework,according to an implementation. Expanding on the explanation above, FIG.3 illustrates that a “By Event” trigger manager 304 reads “By Event”registrations from the trigger persistency 104. Each registration, inaddition to containing a PatternId value, contains a SemantiEventId. Acorresponding field contains a SemantiEvent. Dispatcher 106 determines(for example, every 1 second) if, for these SemanticEventIds, any eventscontaining the corresponding SemanticEvent arrived in the eventpersistency 108. If the determining is TRUE, then a list of suchregistrations is created by the dispatcher 106 to allocated ETD patternsassociated with the registrations to individual threads 110.

Returning to FIG. 1, dispatcher 106 creates triggering threads 110 thatrun independently from dispatcher 110. After threads 110 finishedprocessing their assigned ETD patterns, no return to dispatcher happensand threads end themselves. Once the dispatcher 106 creates threads andpasses PatternIds to the threads 110 to begin execution of correspondingETD patterns, the dispatcher 106's job completes and it is ready to reada next portion of events from event persistency 108. Usually, thedispatcher 106 waits a configured time (for example, 1 second) for thenext reading. In some implementations, the amount of time waited can bemanually determined, dynamically determined, and dynamically-adjustablebased on execution of various components of the ETD triggering framework100, etc.

The threads 110 are typically written in JAVASCRIPT and delegateexecution of ETD patterns to the pattern execution framework 112 (forexample, using a library-to-library in-process communication) fromwithin the same thread 110. In typical implementations, the patternexecution framework 112 is a JAVASCRIPT library that is able to executeETD patterns. If ETD pattern execution returns a findings (particularlyan alert), then the pattern execution framework 112 calls dispatcher 106and passes the PatternId of the ETD pattern whose execution resulted inthe alert. The dispatcher 106 reads the triggering persistency 104 todetermine if there is a registration for triggering “By Pattern” for thePatternId.

If an alert results from the execution of an ETD pattern, patternexecution framework 112 detects the alert and sends a PatternId of theexecuted ETD pattern that caused the alert to the dispatcher 106.

Turning again to FIG. 3, FIG. 3 illustrates a “By Pattern” triggermanager 306. The “By Pattern” trigger manager 306 receives from thepattern execution framework 112 a PatternId of an ETD pattern whoseexecution resulted in alert(s).

In typical implementations, the content of field “TechnicalLogEntryType”in the example event persistence 108 structure above is converted (forexample, name to id) and compared with field “TriggerName” in thetrigger persistency 104. This conversion is typically computationallyvery fast. Note that other methods are possible to determining whetheradditional ETD patterns are registered to be executed following an alertraised when executing an ETD pattern. To the extent other methods areconsistent with this disclosure, they are also considered to be withinthe scope of this disclosure.

If a determination is made that there are additional registered ETDpatterns in the trigger persistency 104 corresponding to the PatternIdreceived by the “By Pattern” trigger manager 306, for each additionaltrigger registration. A distinct thread 110 is allocated by dispatcher106 to execute each ETD pattern associated with the triggerregistration. Each thread 110 delegates the execution of its associatedETD pattern to the pattern execution framework 112. This approach allowsthe definition of chains (workflows) of ETD pattern processing. Usingthis methodology, complex and expensive ETD patterns can be divided intoa chain of simple ETD patterns This division can reduce complexity andallows a chain to be broken/terminated if one of the chained ETDpatterns results in no findings. At some point in the execution of anETD pattern chain, a fork (for example, calling several ETD patternssimultaneously to execute in parallel) can also be performed. Thisforking functionality permits faster execution and receipt of ETDpattern execution results.

Returning to FIG. 1, pattern execution framework 112 can also determineif an alert resulting from an executed ETD pattern was previouslyreported. Pattern execution framework 112 persists alerts along withadditional information (attributes) identifying this alert in a separatepersistency layer (an alert persistency) (not illustrated). If an alertmatches to an alert in the alert persistency, then no additional actionsare done. If the alert does not match to any alerts in the alertpersistency, then the alert is considered as a new alert and thedispatcher 106 receives control information for further processing.Consistent with the explanation above, an alert is a SQL query result (atable) that is returned by a SQL query execution (a pattern execution ona technical layer). Alerts are usually persisted by the patternexecution framework 112 for long periods of time (for example, years)for purposes such as auditability, later proof of a found attack/threat,etc.

In typical implementations, there is a monitoring user interface (notillustrated) for alert monitoring and a user interface for displayingETD pattern execution results (also not illustrated). These userinterfaces read over persisted alerts and execution results and executein separate processes from the triggering framework (see FIG. 3) andpattern execution framework 112.

FIGS. 4B and 4B illustrate a flowchart of an example method 400 (400 a &400 b) for realtime ETD threat detection, according to animplementation. For clarity of presentation, the description thatfollows generally describes method 400 in the context of the otherfigures in this description. However, it will be understood that method400 may be performed, for example, by any suitable system, environment,software, and hardware, or a combination of systems, environments,software, and hardware as appropriate. In some implementations, varioussteps of method 400 can be run in parallel, in combination, in loops, orin any order.

At 402, a saved maximum timestamp is read from the triggeringpersistency and assigned as FromTS. If a maximum timestamp value has notyet been saved, then the MAX timestamp of the logs in the eventspersistency is used instead as the FromTS value. This happens on thevery first dispatcher job run after ETD installation. From 402, method400 proceeds to 404.

At 404, a current maximum timestamp is read from the event persistencyand assigned as ToTS. If there are no events in the event persistency,then the maximum timestamp of the events cannot be retrieved. In thiscase the further processing is skipped and the job loop starts from thebeginning (after waiting of a configured repetition time, for exampleone second). This is likely to happen in an incomplete ETD installationor other anomalous system condition, when the dispatcher job is alreadyrunning, but the event persistency is not yet receiving any logs data.From 404, method 400 proceeds to 406.

At 406, registered triggers of type “By Event” are read from the triggerpersistency. From 406, method 400 proceeds to 408.

At 408, registered trigger content is matched with data from the eventpersistency associated with read events for the time range betweenFromTS and ToTS. From 408, method 408 proceeds to 410.

At 410, a determination is made as to whether read event data matchesregistered trigger content (by pattern) or one or more semantic value(by event) trigger registrations in the triggering persistency (in theregistration list). If it is determined that a match has not occurred,method 400 proceeds to 412. Otherwise, if it is determined that a matchhas occurred, method 200 proceeds to 414.

At 412, the ToTS value is saved as FromTS in the trigger persistency.From 412, method 400 lob loop proceeds back to 402.

At 414, a thread is created for each match and a PatternId is passed toeach thread identifying an ETD pattern to execute. From 414, method 400proceeds to 416.

At 416, two actions are taken: 1) at 412, the ToTS value is saved asFromTS in the trigger persistency and the method 400 job loop proceedsback to 402; and 2) method 400 proceeds to 418 in FIG. 4B.

At 418, the pattern execution framework is delegated the task ofexecuting/processing an ETD pattern by each thread. From 418, method 400proceeds to 420.

At 420, method 420, the pattern execution framework processes the ETDpattern. The pattern execution framework notifies the thread whenprocessing is complete so the thread can terminate. From 420, method 400proceeds to 422.

At 422, the pattern execution framework determines if the execution ofan ETD pattern resulted in an alert. From 422, method 400 proceeds to424.

At 424, a determination is made as to whether an alert occurred from ETDpattern processing. If it is determined that an alert did not occur,method 400 proceeds to 426 where method 400 stops. Otherwise, if it isdetermined that an alert did occur, method 400 proceeds to 428.

At 428, the “By Pattern” trigger manager in the dispatcher is passed thePatternId of the ETD pattern that caused the alert. From 428, method 400proceeds to 430.

At 430, the “By Pattern” trigger manager reads registered “By Pattern”triggers in the trigger persistency. From 430, method 400 proceeds to432.

At 432, the “By Pattern” trigger manager attempts to match registeredtrigger content with the provided PatternId. From 432, method 400proceeds to 434.

At 434, a determination is made as to whether a match exists betweenregistered trigger content and the provided PatternId. If it isdetermined that a match does not exist, method 400 proceeds to 436 wheremethod 400 stops. Otherwise, if it is determined that a match doesexist, method 400 proceeds to 438.

At 438, a thread is created for each match and a PatternId is passed toeach thread identifying an ETD pattern to execute. From 438, method 400proceeds back to 418 to determine if an additional alert occurs from theexecution of the ETD pattern.

FIG. 5 is a block diagram of an exemplary computer system 500 used toprovide computational functionalities associated with describedalgorithms, methods, functions, processes, flows, and procedures asdescribed in the instant disclosure, according to an implementation. Theillustrated computer 502 is intended to encompass any computing devicesuch as a server, desktop computer, laptop/notebook computer, wirelessdata port, smart phone, personal data assistant (PDA), tablet computingdevice, one or more processors within these devices, or any othersuitable processing device, including both physical or virtual instances(or both) of the computing device. Additionally, the computer 502 maycomprise a computer that includes an input device, such as a keypad,keyboard, touch screen, or other device that can accept userinformation, and an output device that conveys information associatedwith the operation of the computer 502, including digital data, visual,or audio information (or a combination of information), or a GUI.

The computer 502 can serve in a role as a client, network component, aserver, a database or other persistency, or any other component (or acombination of roles) of a computer system for performing the subjectmatter described in the instant disclosure. The illustrated computer 502is communicably coupled with a network 530. In some implementations, oneor more components of the computer 502 may be configured to operatewithin environments, including cloud-computing-based, local, global, orother environment (or a combination of environments).

At a high level, the computer 502 is an electronic computing deviceoperable to receive, transmit, process, store, or manage data andinformation associated with the described subject matter. According tosome implementations, the computer 502 may also include or becommunicably coupled with an application server, e-mail server, webserver, caching server, streaming data server, business intelligence(BI) server, or other server (or a combination of servers).

The computer 502 can receive requests over network 530 from a clientapplication (for example, executing on another computer 502) andresponding to the received requests by processing the said requests inan appropriate software application. In addition, requests may also besent to the computer 502 from internal users (for example, from acommand console or by other appropriate access method), external orthird-parties, other automated applications, as well as any otherappropriate entities, individuals, systems, or computers.

Each of the components of the computer 502 can communicate using asystem bus 503. In some implementations, any or all of the components ofthe computer 502, both hardware or software (or a combination ofhardware and software), may interface with each other or the interface504 (or a combination of both) over the system bus 503 using anapplication programming interface (API) 512 or a service layer 513 (or acombination of the API 512 and service layer 513). The API 512 mayinclude specifications for routines, data structures, and objectclasses. The API 512 may be either computer-language independent ordependent and refer to a complete interface, a single function, or evena set of APIs. The service layer 513 provides software services to thecomputer 502 or other components (whether or not illustrated) that arecommunicably coupled to the computer 502. The functionality of thecomputer 502 may be accessible for all service consumers using thisservice layer. Software services, such as those provided by the servicelayer 513, provide reusable, defined business functionalities through adefined interface. For example, the interface may be software written inJAVA, C++, or other suitable language providing data in extensiblemarkup language (XML) format or other suitable format. While illustratedas an integrated component of the computer 502, alternativeimplementations may illustrate the API 512 or the service layer 513 asstand-alone components in relation to other components of the computer502 or other components (whether or not illustrated) that arecommunicably coupled to the computer 502. Moreover, any or all parts ofthe API 512 or the service layer 513 may be implemented as child orsub-modules of another software module, enterprise application, orhardware module without departing from the scope of this disclosure.

The computer 502 includes an interface 504. Although illustrated as asingle interface 504 in FIG. 5, two or more interfaces 504 may be usedaccording to particular needs, desires, or particular implementations ofthe computer 502. The interface 504 is used by the computer 502 forcommunicating with other systems in a distributed environment that areconnected to the network 530 (whether illustrated or not). Generally,the interface 504 comprises logic encoded in software or hardware (or acombination of software and hardware) and operable to communicate withthe network 530. More specifically, the interface 504 may comprisesoftware supporting one or more communication protocols associated withcommunications such that the network 530 or interface's hardware isoperable to communicate physical signals within and outside of theillustrated computer 502.

The computer 502 includes a processor 505. Although illustrated as asingle processor 505 in FIG. 5, two or more processors may be usedaccording to particular needs, desires, or particular implementations ofthe computer 502. Generally, the processor 505 executes instructions andmanipulates data to perform the operations of the computer 502 and anyalgorithms, methods, functions, processes, flows, and procedures asdescribed in the instant disclosure.

The computer 502 also includes a database 506 that can hold data for thecomputer 502 or other components (or a combination of both) that can beconnected to the network 530 (whether illustrated or not). For example,database 506 can be an in-memory, conventional, or other type ofdatabase storing data consistent with this disclosure. In someimplementations, database 506 can be a combination of two or moredifferent database types (for example, a hybrid in-memory andconventional database) according to particular needs, desires, orparticular implementations of the computer 502 and the describedfunctionality. Although illustrated as a single database 506 in FIG. 5,two or more databases (of the same or combination of types) can be usedaccording to particular needs, desires, or particular implementations ofthe computer 502 and the described functionality. While database 506 isillustrated as an integral component of the computer 502, in alternativeimplementations, database 506 can be external to the computer 502.

The computer 502 also includes a memory 507 that can hold data for thecomputer 502 or other components (or a combination of both) that can beconnected to the network 530 (whether illustrated or not). For example,memory 507 can be random access memory (RAM), read-only memory (ROM),optical, magnetic, and the like storing data consistent with thisdisclosure. In some implementations, memory 507 can be a combination oftwo or more different types of memory (for example, a combination of RAMand magnetic storage) according to particular needs, desires, orparticular implementations of the computer 502 and the describedfunctionality. Although illustrated as a single memory 507 in FIG. 5,two or more memories 507 (of the same or combination of types) can beused according to particular needs, desires, or particularimplementations of the computer 502 and the described functionality.While memory 507 is illustrated as an integral component of the computer502, in alternative implementations, memory 507 can be external to thecomputer 502.

The application 508 is an algorithmic software engine providingfunctionality according to particular needs, desires, or particularimplementations of the computer 502, particularly with respect tofunctionality described in this disclosure. For example, application 508can serve as one or more components, modules, applications, etc.Further, although illustrated as a single application 508, theapplication 508 may be implemented as multiple applications 507 on thecomputer 502. In addition, although illustrated as integral to thecomputer 502, in alternative implementations, the application 508 can beexternal to the computer 502.

There may be any number of computers 502 associated with, or externalto, a computer system containing computer 502, each computer 502communicating over network 530. Further, the term “client,” “user,” andother appropriate terminology may be used interchangeably as appropriatewithout departing from the scope of this disclosure. Moreover, thisdisclosure contemplates that many users may use one computer 502, orthat one user may use multiple computers 502.

Described implementations of the subject matter can include one or morefeatures, alone or in combination.

For example, in a first implementation, a computer-implemented method,comprising: generating a trigger registration for a selected triggeringtype; storing the generated trigger registration in a triggeringpersistency; analyzing a received event from an event persistency;comparing data associated with the analyzed event with the triggeringpersistency; and based on the comparison, processing, using a patternexecution framework, an enterprise threat detection (ETD) pattern toperform actions responsive to the received event.

The foregoing and other described implementations can each optionallyinclude one or more of the following features:

A first feature, combinable with any of the following features, whereinthe triggering type includes one of the group consisting of by event andby pattern.

A second feature, combinable with any of the previous or followingfeatures, wherein the trigger registration is stored in a triggeringpersistency registration list.

A third feature, combinable with any of the previous or followingfeatures, comprising determining that the data associated with theanalyzed event matches registered content or one or more semantic valuetrigger registrations in the triggering persistency registration list.

A fourth feature, combinable with any of the previous or followingfeatures, comprising: instantiating a processing thread to process theETD pattern; and delegating the processing of the ETD pattern from theprocessing thread to the pattern execution framework.

A fifth feature, combinable with any of the previous or followingfeatures, comprising determining that execution of the ETD patterngenerates an additional event.

A sixth feature, combinable with any of the previous or followingfeatures, comprising determining whether a triggering registration forthe additional event exists in the triggering persistency.

In a second implementation, a non-transitory, computer-readable mediumstoring one or more instructions executable by a computer system toperform operations comprising: generating a trigger registration for aselected triggering type; storing the generated trigger registration ina triggering persistency; analyzing a received event from an eventpersistency; comparing data associated with the analyzed event with thetriggering persistency; and based on the comparison, processing, using apattern execution framework, an enterprise threat detection (ETD)pattern to perform actions responsive to the received event.

The foregoing and other described implementations can each optionallyinclude one or more of the following features:

A first feature, combinable with any of the following features, whereinthe triggering type includes one of the group consisting of by event andby pattern.

A second feature, combinable with any of the previous or followingfeatures, wherein the trigger registration is stored in a triggeringpersistency registration list.

A third feature, combinable with any of the previous or followingfeatures, comprising one or more instructions to determine that the dataassociated with the analyzed event matches registered content or one ormore semantic value trigger registrations in the triggering persistencyregistration list.

A fourth feature, combinable with any of the previous or followingfeatures, comprising one or more instructions to: instantiate aprocessing thread to process the ETD pattern; and delegate theprocessing of the ETD pattern from the processing thread to the patternexecution framework.

A fifth feature, combinable with any of the previous or followingfeatures, comprising one or more instructions to determine thatexecution of the ETD pattern generates an additional event.

A sixth feature, combinable with any of the previous or followingfeatures, comprising one or more instructions to determine whether atriggering registration for the additional event exists in thetriggering persistency.

In a third implementation, a computer-implemented system, comprising: ahardware processor interoperably coupled with a computer memory andconfigured to perform operations comprising: generating a triggerregistration for a selected triggering type; storing the generatedtrigger registration in a triggering persistency; analyzing a receivedevent from an event persistency; comparing data associated with theanalyzed event with the triggering persistency; and based on thecomparison, processing, using a pattern execution framework, anenterprise threat detection (ETD) pattern to perform actions responsiveto the received event.

The foregoing and other described implementations can each optionallyinclude one or more of the following features:

A first feature, combinable with any of the following features, whereinthe triggering type includes one of the group consisting of by event andby pattern.

A second feature, combinable with any of the previous or followingfeatures, wherein the trigger registration is stored in a triggeringpersistency registration list.

A third feature, combinable with any of the previous or followingfeatures, configured to determine that the data associated with theanalyzed event matches registered content or one or more semantic valuetrigger registrations in the triggering persistency registration list.

A fourth feature, combinable with any of the previous or followingfeatures, configured to: instantiate a processing thread to process theETD pattern; and delegate the processing of the ETD pattern from theprocessing thread to the pattern execution framework.

A fifth feature, combinable with any of the previous or followingfeatures, configured to determine that execution of the ETD patterngenerates an additional event.

A sixth feature, combinable with any of the previous or followingfeatures, configured to determine whether a triggering registration forthe additional event exists in the triggering persistency.

Implementations of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, in tangibly embodied computer software or firmware, incomputer hardware, including the structures disclosed in thisspecification and their structural equivalents, or in combinations ofone or more of them. Implementations of the subject matter described inthis specification can be implemented as one or more computer programs,that is, one or more modules of computer program instructions encoded ona tangible, non-transitory, computer-readable computer-storage mediumfor execution by, or to control the operation of, data processingapparatus. Alternatively or in addition, the program instructions can beencoded on an artificially generated propagated signal, for example, amachine-generated electrical, optical, or electromagnetic signal that isgenerated to encode information for transmission to suitable receiverapparatus for execution by a data processing apparatus. Thecomputer-storage medium can be a machine-readable storage device, amachine-readable storage substrate, a random or serial access memorydevice, or a combination of computer-storage mediums.

The terms “data processing apparatus,” “computer,” or “electroniccomputer device” (or equivalent as understood by one of ordinary skillin the art) refer to data processing hardware and encompass all kinds ofapparatus, devices, and machines for processing data, including by wayof example, a programmable processor, a computer, or multiple processorsor computers. The apparatus can also be or further include specialpurpose logic circuitry, for example, a central processing unit (CPU),an FPGA (field programmable gate array), or an ASIC(application-specific integrated circuit). In some implementations, thedata processing apparatus or special purpose logic circuitry (or acombination of the data processing apparatus or special purpose logiccircuitry) may be hardware- or software-based (or a combination of bothhardware- and software-based). The apparatus can optionally include codethat creates an execution environment for computer programs, forexample, code that constitutes processor firmware, a protocol stack, adatabase management system, an operating system, or a combination ofexecution environments. The present disclosure contemplates the use ofdata processing apparatuses with or without conventional operatingsystems, for example LINUX, UNIX, WINDOWS, MAC OS, ANDROID, IOS, or anyother suitable conventional operating system.

A computer program, which may also be referred to or described as aprogram, software, a software application, a module, a software module,a script, or code can be written in any form of programming language,including compiled or interpreted languages, or declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment. A computer program may, butneed not, correspond to a file in a file system. A program can be storedin a portion of a file that holds other programs or data, for example,one or more scripts stored in a markup language document, in a singlefile dedicated to the program in question, or in multiple coordinatedfiles, for example, files that store one or more modules, sub-programs,or portions of code. A computer program can be deployed to be executedon one computer or on multiple computers that are located at one site ordistributed across multiple sites and interconnected by a communicationnetwork. While portions of the programs illustrated in the variousfigures are shown as individual modules that implement the variousfeatures and functionality through various objects, methods, or otherprocesses, the programs may instead include a number of sub-modules,third-party services, components, libraries, and such, as appropriate.Conversely, the features and functionality of various components can becombined into single components as appropriate.

The processes and logic flows described in this specification can beperformed by one or more programmable computers executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, for example, a CPU, an FPGA, or an ASIC.

Computers suitable for the execution of a computer program can be basedon general or special purpose microprocessors, both, or any other kindof CPU. Generally, a CPU will receive instructions and data from aread-only memory (ROM) or a random access memory (RAM), or both. Theessential elements of a computer are a CPU, for performing or executinginstructions, and one or more memory devices for storing instructionsand data. Generally, a computer will also include, or be operativelycoupled to, receive data from or transfer data to, or both, one or moremass storage devices for storing data, for example, magnetic,magneto-optical disks, or optical disks. However, a computer need nothave such devices. Moreover, a computer can be embedded in anotherdevice, for example, a mobile telephone, a personal digital assistant(PDA), a mobile audio or video player, a game console, a globalpositioning system (GPS) receiver, or a portable storage device, forexample, a universal serial bus (USB) flash drive, to name just a few.

Computer-readable media (transitory or non-transitory, as appropriate)suitable for storing computer program instructions and data include allforms of non-volatile memory, media and memory devices, including by wayof example semiconductor memory devices, for example, erasableprogrammable read-only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), and flash memory devices;magnetic disks, for example, internal hard disks or removable disks;magneto-optical disks; and CD-ROM, DVD+/−R, DVD-RAM, and DVD-ROM disks.The memory may store various objects or data, including caches, classes,frameworks, applications, backup data, jobs, web pages, web pagetemplates, database tables, repositories storing dynamic information,and any other appropriate information including any parameters,variables, algorithms, instructions, rules, constraints, or referencesthereto. Additionally, the memory may include any other appropriatedata, such as logs, policies, security or access data, reporting files,as well as others. The processor and the memory can be supplemented by,or incorporated in, special purpose logic circuitry.

To provide for interaction with a user, implementations of the subjectmatter described in this specification can be implemented on a computerhaving a display device, for example, a CRT (cathode ray tube), LCD(liquid crystal display), LED (Light Emitting Diode), or plasma monitor,for displaying information to the user and a keyboard and a pointingdevice, for example, a mouse, trackball, or trackpad by which the usercan provide input to the computer. Input may also be provided to thecomputer using a touchscreen, such as a tablet computer surface withpressure sensitivity, a multi-touch screen using capacitive or electricsensing, or other type of touchscreen. Other kinds of devices can beused to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, forexample, visual feedback, auditory feedback, or tactile feedback; andinput from the user can be received in any form, including acoustic,speech, or tactile input. In addition, a computer can interact with auser by sending documents to and receiving documents from a device thatis used by the user; for example, by sending web pages to a web browseron a user's client device in response to requests received from the webbrowser.

The term “graphical user interface,” or “GUI,” may be used in thesingular or the plural to describe one or more graphical user interfacesand each of the displays of a particular graphical user interface.Therefore, a GUI may represent any graphical user interface, includingbut not limited to, a web browser, a touch screen, or a command lineinterface (CLI) that processes information and efficiently presents theinformation results to the user. In general, a GUI may include aplurality of user interface (UI) elements, some or all associated with aweb browser, such as interactive fields, pull-down lists, and buttonsoperable by the business suite user. These and other UI elements may berelated to or represent the functions of the web browser.

Implementations of the subject matter described in this specificationcan be implemented in a computing system that includes a back-endcomponent, for example, as a data server, or that includes a middlewarecomponent, for example, an application server, or that includes afront-end component, for example, a client computer having a graphicaluser interface or a Web browser through which a user can interact withan implementation of the subject matter described in this specification,or any combination of one or more such back-end, middleware, orfront-end components. The components of the system can be interconnectedby any form or medium of wireline or wireless digital data communication(or a combination of data communication), for example, a communicationnetwork. Examples of communication networks include a local area network(LAN), a radio access network (RAN), a metropolitan area network (MAN),a wide area network (WAN), Worldwide Interoperability for MicrowaveAccess (WIMAX), a wireless local area network (WLAN) using, for example,802.11 a/b/g/n or 802.20 (or a combination of 802.11x and 802.20 orother protocols consistent with this disclosure), all or a portion ofthe Internet, or any other communication system or systems at one ormore locations (or a combination of communication networks). The networkmay communicate with, for example, Internet Protocol (IP) packets, FrameRelay frames, Asynchronous Transfer Mode (ATM) cells, voice, video,data, or other suitable information (or a combination of communicationtypes) between network addresses.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

In some implementations, any or all of the components of the computingsystem, both hardware or software (or a combination of hardware andsoftware), may interface with each other or the interface using anapplication programming interface (API) or a service layer (or acombination of API and service layer). The API may includespecifications for routines, data structures, and object classes. TheAPI may be either computer language independent or dependent and referto a complete interface, a single function, or even a set of APIs. Theservice layer provides software services to the computing system. Thefunctionality of the various components of the computing system may beaccessible for all service consumers using this service layer. Softwareservices provide reusable, defined business functionalities through adefined interface. For example, the interface may be software written inJAVA, C++, or other suitable language providing data in extensiblemarkup language (XML) format or other suitable format. The API orservice layer (or a combination of the API and the service layer) may bean integral or a stand-alone component in relation to other componentsof the computing system. Moreover, any or all parts of the service layermay be implemented as child or sub-modules of another software module,enterprise application, or hardware module without departing from thescope of this disclosure.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinvention or on the scope of what may be claimed, but rather asdescriptions of features that may be specific to particularimplementations of particular inventions. Certain features that aredescribed in this specification in the context of separateimplementations can also be implemented, in combination, in a singleimplementation. Conversely, various features that are described in thecontext of a single implementation can also be implemented in multipleimplementations, separately, or in any suitable sub-combination.Moreover, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can, in some cases, be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Particular implementations of the subject matter have been described.Other implementations, alterations, and permutations of the describedimplementations are within the scope of the following claims as will beapparent to those skilled in the art. While operations are depicted inthe drawings or claims in a particular order, this should not beunderstood as requiring that such operations be performed in theparticular order shown or in sequential order, or that all illustratedoperations be performed (some operations may be considered optional), toachieve desirable results. In certain circumstances, multitasking orparallel processing (or a combination of multitasking and parallelprocessing) may be advantageous and performed as deemed appropriate.

Moreover, the separation or integration of various system modules andcomponents in the implementations described above should not beunderstood as requiring such separation or integration in allimplementations, and it should be understood that the described programcomponents and systems can generally be integrated together in a singlesoftware product or packaged into multiple software products.

Accordingly, the above description of example implementations does notdefine or constrain this disclosure. Other changes, substitutions, andalterations are also possible without departing from the spirit andscope of this disclosure.

Furthermore, any claimed implementation below is considered to beapplicable to at least a computer-implemented method; a non-transitory,computer-readable medium storing computer-readable instructions toperform the computer-implemented method; and a computer systemcomprising a computer memory interoperably coupled with a hardwareprocessor configured to perform the computer-implemented method or theinstructions stored on the non-transitory, computer-readable medium.

What is claimed is:
 1. A computer-implemented method, comprising:generating a trigger registration for a selected triggering type;storing the generated trigger registration in a triggering persistency;analyzing a received event from an event persistency; comparing dataassociated with the analyzed event with the triggering persistency; andbased on the comparison, processing, using a pattern executionframework, an enterprise threat detection (ETD) pattern data object toperform actions responsive to the received event, wherein the ETDpattern is translated into a structured query language (SQL) query, andwherein the ETD pattern contains paths connected over references andeach path contains subsets representing conditions; and upon detectionof an alert based on processing of the ETD pattern, transmitting apattern identification of the ETD pattern to a high-frequencycomputational daemon thread or a job which processes one or more otherETD patterns corresponding to the ETD pattern in parallel and bytriggering separate processing threads to execute each other ETDpattern, wherein each separate processing thread completes processing ofa particular other ETD pattern and ends with no return to thehigh-frequency computational daemon thread or the job.
 2. Thecomputer-implemented method of claim 1, wherein the triggering typeincludes one of the group consisting of by event and by pattern.
 3. Thecomputer-implemented method of claim 1, wherein the trigger registrationis stored in a triggering persistency registration list.
 4. Thecomputer-implemented method of claim 3, comprising determining that thedata associated with the analyzed event matches registered content orone or more semantic value trigger registrations in the triggeringpersistency registration list.
 5. The computer-implemented method ofclaim 1, comprising: instantiating a processing thread to process theETD pattern; and delegating the processing of the ETD pattern from theprocessing thread to the pattern execution framework.
 6. Thecomputer-implemented method of claim 1, comprising determining thatexecution of the ETD pattern generates an additional event.
 7. Thecomputer-implemented method of claim 6, comprising determining whether atriggering registration for the additional event exists in thetriggering persistency.
 8. A non-transitory, computer-readable mediumstoring one or more instructions executable by a computer system toperform operations comprising: generating a trigger registration for aselected triggering type; storing the generated trigger registration ina triggering persistency; analyzing a received event from an eventpersistency; comparing data associated with the analyzed event with thetriggering persistency; and based on the comparison, processing, using apattern execution framework, an enterprise threat detection (ETD)pattern data object to perform actions responsive to the received event,wherein the ETD pattern is translated into a structured query language(SQL) query, and wherein the ETD pattern contains paths connected overreferences and each path contains subsets representing conditions; andupon detection of an alert based on processing of the ETD pattern,transmitting a pattern identification of the ETD pattern to ahigh-frequency computational daemon thread or a job which processes oneor more other ETD patterns corresponding to the ETD pattern in paralleland by triggering separate processing threads to execute each other ETDpattern, wherein each separate processing thread completes processing ofa particular other ETD pattern and ends with no return to thehigh-frequency computational daemon thread or the job.
 9. Thenon-transitory, computer-readable medium of claim 8, wherein thetriggering type includes one of the group consisting of by event and bypattern.
 10. The non-transitory, computer-readable medium of claim 8,wherein the trigger registration is stored in a triggering persistencyregistration list.
 11. The non-transitory, computer-readable medium ofclaim 10, comprising one or more instructions to determine that the dataassociated with the analyzed event matches registered content or one ormore semantic value trigger registrations in the triggering persistencyregistration list.
 12. The non-transitory, computer-readable medium ofclaim 8, comprising one or more instructions to: instantiate aprocessing thread to process the ETD pattern; and delegate theprocessing of the ETD pattern from the processing thread to the patternexecution framework.
 13. The non-transitory, computer-readable medium ofclaim 8, comprising one or more instructions to determine that executionof the ETD pattern generates an additional event.
 14. Thenon-transitory, computer-readable medium of claim 13, comprising one ormore instructions to determine whether a triggering registration for theadditional event exists in the triggering persistency.
 15. Acomputer-implemented system, comprising: a hardware processorinteroperably coupled with a computer memory and configured to performoperations comprising: generating a trigger registration for a selectedtriggering type; storing the generated trigger registration in atriggering persistency; analyzing a received event from an eventpersistency; comparing data associated with the analyzed event with thetriggering persistency; and based on the comparison, processing, using apattern execution framework, an enterprise threat detection (ETD)pattern data object to perform actions responsive to the received event,wherein the ETD pattern is translated into a structured query language(SQL) query, and wherein the ETD pattern contains paths connected overreferences and each path contains subsets representing conditions; andupon detection of an alert based on processing of the ETD pattern,transmitting a pattern identification of the ETD pattern to ahigh-frequency computational daemon thread or a lob which processes oneor more other ETD patterns corresponding to the ETD pattern in paralleland by triggering separate processing threads to execute each other ETDpattern, wherein each separate processing thread completes processing ofa particular other ETD pattern and ends with no return to thehigh-frequency computational daemon thread or the job.
 16. Thecomputer-implemented system of claim 15, wherein the triggering typeincludes one of the group consisting of by event and by pattern.
 17. Thecomputer-implemented system of claim 15, wherein the triggerregistration is stored in a triggering persistency registration list.18. The computer-implemented system of claim 17, configured to determinethat the data associated with the analyzed event matches registeredcontent or one or more semantic value trigger registrations in thetriggering persistency registration list.
 19. The computer-implementedsystem of claim 15, configured to: instantiate a processing thread toprocess the ETD pattern; and delegate the processing of the ETD patternfrom the processing thread to the pattern execution framework.
 20. Thecomputer-implemented system of claim 15, configured to: determine thatexecution of the ETD pattern generates an additional event; anddetermine whether a triggering registration for the additional eventexists in the triggering persistency.